SOTAVerified

Relational Reasoning

The goal of Relational Reasoning is to figure out the relationships among different entities, such as image pixels, words or sentences, human skeletons or interactive moving agents.

Source: Social-WaGDAT: Interaction-aware Trajectory Prediction via Wasserstein Graph Double-Attention Network

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 271–280 of 483 papers

TitleStatusHype
RelTextRank: An Open Source Framework for Building Relational Syntactic-Semantic Text Pair Representations—0
Representational Alignment with Chemical Induced Fit for Molecular Relational Learning—0
Retrieval-based Knowledge Augmented Vision Language Pre-training—0
ReVoLT: Relational Reasoning and Voronoi Local Graph Planning for Target-driven Navigation—0
SAG-VAE: End-to-end Joint Inference of Data Representations and Feature Relations—0
Sampling Community Structure—0
SARN: Relational Reasoning through Sequential Attention—0
Scalable Statistical Relational Learning for NLP—0
Schema Independent Relational Learning—0
SCR-Graph: Spatial-Causal Relationships based Graph Reasoning Network for Human Action Prediction—0
Show:102550
← PrevPage 28 of 49Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified